



'''simple docstring'''





from collections import OrderedDict

from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES


lowercase_									=    logging.get_logger(__name__)


lowercase_									=    OrderedDict(
    [
        # Base model mapping
        ("albert", "FlaxAlbertModel"),
        ("bart", "FlaxBartModel"),
        ("beit", "FlaxBeitModel"),
        ("bert", "FlaxBertModel"),
        ("big_bird", "FlaxBigBirdModel"),
        ("blenderbot", "FlaxBlenderbotModel"),
        ("blenderbot-small", "FlaxBlenderbotSmallModel"),
        ("clip", "FlaxCLIPModel"),
        ("distilbert", "FlaxDistilBertModel"),
        ("electra", "FlaxElectraModel"),
        ("gpt-sw3", "FlaxGPT2Model"),
        ("gpt2", "FlaxGPT2Model"),
        ("gpt_neo", "FlaxGPTNeoModel"),
        ("gptj", "FlaxGPTJModel"),
        ("longt5", "FlaxLongT5Model"),
        ("marian", "FlaxMarianModel"),
        ("mbart", "FlaxMBartModel"),
        ("mt5", "FlaxMT5Model"),
        ("opt", "FlaxOPTModel"),
        ("pegasus", "FlaxPegasusModel"),
        ("regnet", "FlaxRegNetModel"),
        ("resnet", "FlaxResNetModel"),
        ("roberta", "FlaxRobertaModel"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormModel"),
        ("roformer", "FlaxRoFormerModel"),
        ("t5", "FlaxT5Model"),
        ("vision-text-dual-encoder", "FlaxVisionTextDualEncoderModel"),
        ("vit", "FlaxViTModel"),
        ("wav2vec2", "FlaxWav2Vec2Model"),
        ("whisper", "FlaxWhisperModel"),
        ("xglm", "FlaxXGLMModel"),
        ("xlm-roberta", "FlaxXLMRobertaModel"),
    ]
)

lowercase_									=    OrderedDict(
    [
        # Model for pre-training mapping
        ("albert", "FlaxAlbertForPreTraining"),
        ("bart", "FlaxBartForConditionalGeneration"),
        ("bert", "FlaxBertForPreTraining"),
        ("big_bird", "FlaxBigBirdForPreTraining"),
        ("electra", "FlaxElectraForPreTraining"),
        ("longt5", "FlaxLongT5ForConditionalGeneration"),
        ("mbart", "FlaxMBartForConditionalGeneration"),
        ("mt5", "FlaxMT5ForConditionalGeneration"),
        ("roberta", "FlaxRobertaForMaskedLM"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForMaskedLM"),
        ("roformer", "FlaxRoFormerForMaskedLM"),
        ("t5", "FlaxT5ForConditionalGeneration"),
        ("wav2vec2", "FlaxWav2Vec2ForPreTraining"),
        ("whisper", "FlaxWhisperForConditionalGeneration"),
        ("xlm-roberta", "FlaxXLMRobertaForMaskedLM"),
    ]
)

lowercase_									=    OrderedDict(
    [
        # Model for Masked LM mapping
        ("albert", "FlaxAlbertForMaskedLM"),
        ("bart", "FlaxBartForConditionalGeneration"),
        ("bert", "FlaxBertForMaskedLM"),
        ("big_bird", "FlaxBigBirdForMaskedLM"),
        ("distilbert", "FlaxDistilBertForMaskedLM"),
        ("electra", "FlaxElectraForMaskedLM"),
        ("mbart", "FlaxMBartForConditionalGeneration"),
        ("roberta", "FlaxRobertaForMaskedLM"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForMaskedLM"),
        ("roformer", "FlaxRoFormerForMaskedLM"),
        ("xlm-roberta", "FlaxXLMRobertaForMaskedLM"),
    ]
)

lowercase_									=    OrderedDict(
    [
        # Model for Seq2Seq Causal LM mapping
        ("bart", "FlaxBartForConditionalGeneration"),
        ("blenderbot", "FlaxBlenderbotForConditionalGeneration"),
        ("blenderbot-small", "FlaxBlenderbotSmallForConditionalGeneration"),
        ("encoder-decoder", "FlaxEncoderDecoderModel"),
        ("longt5", "FlaxLongT5ForConditionalGeneration"),
        ("marian", "FlaxMarianMTModel"),
        ("mbart", "FlaxMBartForConditionalGeneration"),
        ("mt5", "FlaxMT5ForConditionalGeneration"),
        ("pegasus", "FlaxPegasusForConditionalGeneration"),
        ("t5", "FlaxT5ForConditionalGeneration"),
    ]
)

lowercase_									=    OrderedDict(
    [
        # Model for Image-classsification
        ("beit", "FlaxBeitForImageClassification"),
        ("regnet", "FlaxRegNetForImageClassification"),
        ("resnet", "FlaxResNetForImageClassification"),
        ("vit", "FlaxViTForImageClassification"),
    ]
)

lowercase_									=    OrderedDict(
    [
        ("vision-encoder-decoder", "FlaxVisionEncoderDecoderModel"),
    ]
)

lowercase_									=    OrderedDict(
    [
        # Model for Causal LM mapping
        ("bart", "FlaxBartForCausalLM"),
        ("bert", "FlaxBertForCausalLM"),
        ("big_bird", "FlaxBigBirdForCausalLM"),
        ("electra", "FlaxElectraForCausalLM"),
        ("gpt-sw3", "FlaxGPT2LMHeadModel"),
        ("gpt2", "FlaxGPT2LMHeadModel"),
        ("gpt_neo", "FlaxGPTNeoForCausalLM"),
        ("gptj", "FlaxGPTJForCausalLM"),
        ("opt", "FlaxOPTForCausalLM"),
        ("roberta", "FlaxRobertaForCausalLM"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForCausalLM"),
        ("xglm", "FlaxXGLMForCausalLM"),
        ("xlm-roberta", "FlaxXLMRobertaForCausalLM"),
    ]
)

lowercase_									=    OrderedDict(
    [
        # Model for Sequence Classification mapping
        ("albert", "FlaxAlbertForSequenceClassification"),
        ("bart", "FlaxBartForSequenceClassification"),
        ("bert", "FlaxBertForSequenceClassification"),
        ("big_bird", "FlaxBigBirdForSequenceClassification"),
        ("distilbert", "FlaxDistilBertForSequenceClassification"),
        ("electra", "FlaxElectraForSequenceClassification"),
        ("mbart", "FlaxMBartForSequenceClassification"),
        ("roberta", "FlaxRobertaForSequenceClassification"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForSequenceClassification"),
        ("roformer", "FlaxRoFormerForSequenceClassification"),
        ("xlm-roberta", "FlaxXLMRobertaForSequenceClassification"),
    ]
)

lowercase_									=    OrderedDict(
    [
        # Model for Question Answering mapping
        ("albert", "FlaxAlbertForQuestionAnswering"),
        ("bart", "FlaxBartForQuestionAnswering"),
        ("bert", "FlaxBertForQuestionAnswering"),
        ("big_bird", "FlaxBigBirdForQuestionAnswering"),
        ("distilbert", "FlaxDistilBertForQuestionAnswering"),
        ("electra", "FlaxElectraForQuestionAnswering"),
        ("mbart", "FlaxMBartForQuestionAnswering"),
        ("roberta", "FlaxRobertaForQuestionAnswering"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForQuestionAnswering"),
        ("roformer", "FlaxRoFormerForQuestionAnswering"),
        ("xlm-roberta", "FlaxXLMRobertaForQuestionAnswering"),
    ]
)

lowercase_									=    OrderedDict(
    [
        # Model for Token Classification mapping
        ("albert", "FlaxAlbertForTokenClassification"),
        ("bert", "FlaxBertForTokenClassification"),
        ("big_bird", "FlaxBigBirdForTokenClassification"),
        ("distilbert", "FlaxDistilBertForTokenClassification"),
        ("electra", "FlaxElectraForTokenClassification"),
        ("roberta", "FlaxRobertaForTokenClassification"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForTokenClassification"),
        ("roformer", "FlaxRoFormerForTokenClassification"),
        ("xlm-roberta", "FlaxXLMRobertaForTokenClassification"),
    ]
)

lowercase_									=    OrderedDict(
    [
        # Model for Multiple Choice mapping
        ("albert", "FlaxAlbertForMultipleChoice"),
        ("bert", "FlaxBertForMultipleChoice"),
        ("big_bird", "FlaxBigBirdForMultipleChoice"),
        ("distilbert", "FlaxDistilBertForMultipleChoice"),
        ("electra", "FlaxElectraForMultipleChoice"),
        ("roberta", "FlaxRobertaForMultipleChoice"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForMultipleChoice"),
        ("roformer", "FlaxRoFormerForMultipleChoice"),
        ("xlm-roberta", "FlaxXLMRobertaForMultipleChoice"),
    ]
)

lowercase_									=    OrderedDict(
    [
        ("bert", "FlaxBertForNextSentencePrediction"),
    ]
)

lowercase_									=    OrderedDict(
    [
        ("speech-encoder-decoder", "FlaxSpeechEncoderDecoderModel"),
        ("whisper", "FlaxWhisperForConditionalGeneration"),
    ]
)

lowercase_									=    OrderedDict(
    [
        ("whisper", "FlaxWhisperForAudioClassification"),
    ]
)

lowercase_									=    _LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_MAPPING_NAMES)
lowercase_									=    _LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_PRETRAINING_MAPPING_NAMES)
lowercase_									=    _LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_MASKED_LM_MAPPING_NAMES)
lowercase_									=    _LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES
)
lowercase_									=    _LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES
)
lowercase_									=    _LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES)
lowercase_									=    _LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_CAUSAL_LM_MAPPING_NAMES)
lowercase_									=    _LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES
)
lowercase_									=    _LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES
)
lowercase_									=    _LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES
)
lowercase_									=    _LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES
)
lowercase_									=    _LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING_NAMES
)
lowercase_									=    _LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES
)
lowercase_									=    _LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES
)






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			Dict		=			FLAX_MODEL_MAPPING





lowercase_									=    auto_class_update(FlaxAutoModel)






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			List[Any]		=			FLAX_MODEL_FOR_PRETRAINING_MAPPING





lowercase_									=    auto_class_update(FlaxAutoModelForPreTraining, head_doc="pretraining")






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			int		=			FLAX_MODEL_FOR_CAUSAL_LM_MAPPING





lowercase_									=    auto_class_update(FlaxAutoModelForCausalLM, head_doc="causal language modeling")






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			Optional[Any]		=			FLAX_MODEL_FOR_MASKED_LM_MAPPING





lowercase_									=    auto_class_update(FlaxAutoModelForMaskedLM, head_doc="masked language modeling")






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			Optional[Any]		=			FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING





lowercase_									=    auto_class_update(
    FlaxAutoModelForSeqaSeqLM, head_doc="sequence-to-sequence language modeling", checkpoint_for_example="t5-base"
)






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			Any		=			FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING





lowercase_									=    auto_class_update(
    FlaxAutoModelForSequenceClassification, head_doc="sequence classification"
)






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			Optional[int]		=			FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING





lowercase_									=    auto_class_update(FlaxAutoModelForQuestionAnswering, head_doc="question answering")






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			Optional[int]		=			FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING





lowercase_									=    auto_class_update(
    FlaxAutoModelForTokenClassification, head_doc="token classification"
)






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			str		=			FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING





lowercase_									=    auto_class_update(FlaxAutoModelForMultipleChoice, head_doc="multiple choice")






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			Tuple		=			FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING





lowercase_									=    auto_class_update(
    FlaxAutoModelForNextSentencePrediction, head_doc="next sentence prediction"
)






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			str		=			FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING





lowercase_									=    auto_class_update(
    FlaxAutoModelForImageClassification, head_doc="image classification"
)






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			Optional[int]		=			FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING





lowercase_									=    auto_class_update(FlaxAutoModelForVisionaSeq, head_doc="vision-to-text modeling")






class __A     (    _BaseAutoModelClass		):



 '''simple docstring'''







 __lowerCamelCase       :			Any		=			FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING





lowercase_									=    auto_class_update(
    FlaxAutoModelForSpeechSeqaSeq, head_doc="sequence-to-sequence speech-to-text modeling"
)








'''simple docstring'''






from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType

class 				a__(   lowerCamelCase__      ):
    lowercase__					=       ["""image_processor""", """tokenizer"""]
    lowercase__					=       """BridgeTowerImageProcessor"""
    lowercase__					=       ("""RobertaTokenizer""", """RobertaTokenizerFast""")







    def __init__( self					:    int		,     __snake_case					:    str		,     __snake_case					:    List[str]      ):
      super().__init__(__snake_case		,     __snake_case      )







    def __call__( self					:    int		,     __snake_case					:    Optional[Any]		,     __snake_case					:    Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None		,     __snake_case					:    bool = True		,     __snake_case					:    Union[bool, str, PaddingStrategy] = False		,     __snake_case					:    Union[bool, str, TruncationStrategy] = None		,     __snake_case					:    Optional[int] = None		,     __snake_case					:    int = 0		,     __snake_case					:    Optional[int] = None		,     __snake_case					:    Optional[bool] = None		,     __snake_case					:    Optional[bool] = None		,     __snake_case					:    bool = False		,     __snake_case					:    bool = False		,     __snake_case					:    bool = False		,     __snake_case					:    bool = False		,     __snake_case					:    bool = True		,     __snake_case					:    Optional[Union[str, TensorType]] = None		,     **__snake_case					:    List[Any]		,     ):
      a		:   Optional[int]	  =	self.tokenizer(
          text=__snake_case		,     add_special_tokens=__snake_case		,     padding=__snake_case		,     truncation=__snake_case		,     max_length=__snake_case		,     stride=__snake_case		,     pad_to_multiple_of=__snake_case		,     return_token_type_ids=__snake_case		,     return_attention_mask=__snake_case		,     return_overflowing_tokens=__snake_case		,     return_special_tokens_mask=__snake_case		,     return_offsets_mapping=__snake_case		,     return_length=__snake_case		,     verbose=__snake_case		,     return_tensors=__snake_case		,     **__snake_case		,     )
      # add pixel_values + pixel_mask
      a		:   List[str]	  =	self.image_processor(
          __snake_case		,     return_tensors=__snake_case		,     do_normalize=__snake_case		,     do_center_crop=__snake_case		,     **__snake_case      )
      encoding.update(__snake_case      )

      return encoding







    def      lowercase_			( self					:    int		,     *__snake_case					:    List[str]		,     **__snake_case					:    List[str]      ):
      return self.tokenizer.batch_decode(*__snake_case		,     **__snake_case      )







    def      lowercase_			( self					:    List[str]		,     *__snake_case					:    Tuple		,     **__snake_case					:    Union[str, Any]      ):
      return self.tokenizer.decode(*__snake_case		,     **__snake_case      )







    @property
    def      lowercase_			( self					:    Optional[Any]      ):
      a		:   Optional[Any]	  =	self.tokenizer.model_input_names
      a		:   Union[str, Any]	  =	self.image_processor.model_input_names
      return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names      )      )